tkmt-package 0.1

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tkmt-package

tkmt-package is a Python library for dealing with regression problem statements.This package includes modules for ensemble learning starting from data preparation to assign the dependent and independent variables, data normalization to rescale the data, train test split.There are modules for setting user defined base models to use ensemble learning techniques like averaging and weighted averaging.The module for the accuracy filter, filters out and displays the modules with the accuracy more than or equal to the set user defined threshold value.There is a module to get weights of the models defined by the user based on their accuracies. The module for averaging technique takes the average of the performance of all the models defined by the user and outputs a new model based on the average Similarly, the module for weighted averaging technique, takes the average of all the models based on their weights. The module for performance evaluation gives shows the performance of the model in terms of accuracy, MAE, MSE, MAPE and RMSE. The performance of the models is plotted using the get_plot module in terms of real and predicted values

Installation

Use the package manager pip to install foobar.

pip install tkmt-package

Main Features

Ensemble Learning Techniques:

• Averaging
• Weighted Averaging
• Rank Weighted

Data Preprocessing:

• Data Preperation
• Data Normalizations
• Train TEST Split
• Performance Evaluation
• Graphical Representation

Documentation

The documentation for the latest release is at

• https://github.com/tkmtpackage?tab=repositories

How to get it

The main branch on GitHub is the most up to date code

• https://github.com/tkmtpackage?tab=repositories

Source download of release tags are available on GitHub

• https://github.com/tkmtpackage?tab=repositories

Contributing

Contributions in any form are welcome, including:

• Documentation improvements
• Additional tests
• New features to existing models
• New models